基于Elman神经网络的汽油机瞬态空燃比辨识

Z. Hou, Quntai Sen, Yihu Wu
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引用次数: 11

摘要

空燃比是影响汽油机动力性能、燃油经济性和废气排放的关键指标,其精确模型是精确空燃比控制的基础。以HL495发动机为实验装置,提出了一种基于Elman神经网络的压缩空燃比方法。实验结果表明,基于Elman神经网络的空燃比模型结构简单,能较准确地逼近空燃比瞬态过程,平均相对误差小于1%。基于Elman神经网络的空气燃料比模型优于基于BP神经网络的空气燃料比模型
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Air Fuel Ratio Identification of Gasoline Engine during Transient Conditions Based on Elman Neural Networks
Air fuel ratio is a key index affecting power performance and fuel economy and exhaust emissions of the gasoline engine, whose accurate model is the foundation of accuracy air fuel ratio control. Taking HL495 engine as experimental device, a method of indenting air fuel ratio based on Elman neural network was provided in this paper. Experiment results show the air fuel ratio model based on Elman neural network has simple structure and can accurately approximate the air fuel ratio transient process and average relative error is less than 1 %. The air fuel ratio based on Elman neural network is better than the air fuel ratio model based on BP neural network
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